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I'm looking for a developer to build an initial proof of concept for a digital twin platform for lifts/elevators.

The aim is to create a visual interface that connects to lift data and uses Grafana to display live operating status, floor position, faults, performance and historical data.

I want a basic working prototype that can eventually scale to multiple lifts and buildings. Initially, simulated data is acceptable if real lift data integration is not immediately possible.

Required skills: Grafana, MQTT/API integration, InfluxDB or similar time-series databases, backend development, and digital twin interface development. Experience with industrial IoT is essential.

My initial budget is around £500, so I'm looking for someone who can deliver a small, clearly defined prototype and advise on the best architecture for future development.

Please provide examples of relevant projects, your proposed approach, and what you could realistically deliver within this budget.

I would like to own the source code and documentation on completion.


Thanks,
Fraser

We are building a multi-tenant SaaS platform with a mobile-first web app, an iOS mobile app, location-based features, subscription billing, a media delivery service, healthcare data integrations and an AI assistant. We have a product spec and an early prototype. We need an engineer, or a small team led by one engineer, to take it through four fixed-price milestones. We care about a working demo at each milestone, not just code we cannot evaluate.

PROJECT SCOPE

Milestone 1: Foundations and Architecture

Review the existing prototype and codebase and give us a written assessment: what exists, what is missing, and the recommended path forward.
Set up dev, staging and production on AWS (ECS, Fargate, EC2, VPC, IAM) with Pulumi for infrastructure as code.
Build CI/CD with GitHub, Jenkins or GoCD, and AWS CodePipeline and CodeDeploy.
Create the data layer on PostgreSQL (Aurora) and Redis, with MySQL, MongoDB and DynamoDB where each fits.
Build authentication: magic-link login, JWT, API keys, role-based permissions, admin MFA and rate limiting.

Milestone 2: Core Product

Web app: Next.js (App Router), React, TypeScript and Tailwind CSS, plus an Angular admin dashboard.
Mobile app: Flutter (Dart) or React Native for iOS, with push notifications and App Store submission.
Backend services: Go 1.20+ (Gin, Gorm, goroutines, channels, gRPC) and a Node.js/NestJS API layer with Prisma.
Real-time features: presence and live updates with Elixir and Phoenix channels.
Location features: interactive map with Leaflet and OpenStreetMap, plus GPS proximity detection.
Admin tools: a content back-office that needs no code changes.

Milestone 3: Payments, Contracts and Integrations

Payments: subscriptions and one-time purchases with Stripe, Paddle and PayPal behind one internal payment interface, including webhooks with signature verification, idempotency, refunds and failure handling.
E-signing: Oneflow or Scrive integration for electronic contracts, with the architecture ready for BankID and ID06.
Healthcare: EHR integration using FHIR and HL7 standards.
Background work: message queues and asynchronous jobs.
Legacy and third-party: a legacy PHP module to integrate with, plus third-party APIs.
Media: a streaming service (HLS and DASH, transcoding) running on a Linux VPS. A Rust worker for the transcoding path is welcome.

Milestone 4: AI, Hardening and Handover

AI service in Python with FastAPI: LLM integration, RAG, and agents using LangChain, LangGraph or the OpenAI Agents SDK. Content ingestion uses Python-Goose, and early workflow prototypes may be done in Stack AI.
Observability: Prometheus, Grafana and Datadog.
Orchestration: Docker and Docker Compose for local and staging, Kubernetes for production (EKS on AWS, GKE and Compute Engine on GCP).
Security and compliance: GDPR workflows, encryption at rest and in transit, EU hosting (AWS Stockholm), audit logs and anti-scraping controls.
Testing: Jest, Playwright and Go tests on core business logic.
Handover: source code in our GitHub, documentation and a walkthrough call.

TECHNOLOGY REFERENCE
Languages: Go, Python, JavaScript, TypeScript, Dart, Elixir, Rust, PHP.
Frontend: React, Next.js, Angular, Tailwind CSS, Leaflet/OpenStreetMap.
Mobile: Flutter, React Native, iOS, push notifications.
Backend: Gin, Gorm, FastAPI, Node.js, NestJS, Prisma, Phoenix, gRPC, REST.
Databases: PostgreSQL, Aurora, MySQL, MongoDB, DynamoDB, Redis.
Cloud and DevOps: AWS (ECS, Fargate, EKS, EC2, VPC, IAM, CodeDeploy, CodePipeline), GCP (GKE, Compute Engine), Docker, Docker Compose, Kubernetes, Pulumi, Jenkins, GoCD, GitHub, Linux.
Payments and contracts: Stripe, Paddle, PayPal, Oneflow, Scrive, BankID, ID06.
AI: LLMs, RAG, AI agents, LangChain, LangGraph, OpenAI Agents SDK, Stack AI, Python-Goose.
Observability: Prometheus, Grafana, Datadog.
Testing: Jest, Playwright.
Media and health: HLS, DASH, FHIR, HL7.

WHAT WE NEED FROM YOU

A short description of a past project that combined at least two of: accounts, maps, payments, real-time features or AI.
Which of the technologies above you have used in production, which you have not, and how you would close the gaps.
Your fixed price and timeline per milestone, your availability and your time zone.
Links to a GitHub profile or live work.

We are looking for a senior (Principal / Staff+ level) engineer to architect, build, secure and operate production-grade autonomous multi-agent AI systems. This is a long-term engagement on real production systems with real uptime requirements, not a chatbot, demo or no-code automation.

WHAT YOU WILL BUILD
• Multi-agent systems with planner, executor, supervisor, worker and critic agents (LangGraph or custom)
• Event-driven, durable workflows that run for hours or days and recover from any failure (Temporal, Celery, Kafka, NATS)
• Inference and model-routing infrastructure optimized for cost and latency (vLLM, Ray, OpenAI and Anthropic APIs)
• Persistent memory and advanced retrieval: Postgres, Redis, pgvector, Neo4j, Graph RAG, hybrid search
• Tool and enterprise integrations via MCP and APIs (Salesforce, SAP, ServiceNow, Oracle, Workday)
• Human-in-the-loop controls: escalation, approvals, confidence thresholds and override
• Evaluation, monitoring and audit logging for every agent decision (LangSmith, OpenTelemetry, Prometheus, Grafana)
• Deployment on Docker, Kubernetes and Terraform across AWS, Azure or GCP

REQUIREMENTS
• Proven experience building and operating autonomous or multi-agent systems in real production
• Ability to own the full system: architecture, infrastructure, deployment, security, evaluation and reliability
• Strong distributed systems skills: idempotency, retries, replay, backpressure, fault tolerance
• Security-first approach: prompt injection, tool abuse, memory poisoning and access control
• Deep async Python (asyncio, concurrency, queues)
• Experience setting and meeting reliability targets (SLOs) for latency, uptime and cost
• Production integration experience with at least two of Salesforce, SAP, ServiceNow, Oracle or Workday
• Able to work independently without a technical lead

PLEASE DO NOT BID IF
Your main experience is chatbot wrappers, simple RAG apps, Streamlit demos, no-code workflows or prompt engineering only.

PROJECT STAGES
1. Paid 90-minute live architecture review
2. Paid 3–4 hour live build of a working multi-agent system (it must run)
3. Review call on a production system you have built
4. Live security and reliability review of your design
5. Ongoing long-term work

HOW TO BID
Bids without these will not be considered:
1. Your GitHub and LinkedIn links
2. The most impressive autonomous system you have shipped, your role, and what runs in production today
3. The hardest production failure you fixed and how you prevented it from happening again
4. Your hourly rate and weekly availability

We are looking for a senior (Principal / Staff+ level) engineer to architect, build, secure and operate production-grade autonomous multi-agent AI systems. This is a long-term engagement on real production systems with real uptime requirements, not a chatbot, demo or no-code automation.

WHAT YOU WILL BUILD
• Multi-agent systems with planner, executor, supervisor, worker and critic agents (LangGraph or custom)
• Event-driven, durable workflows that run for hours or days and recover from any failure (Temporal, Celery, Kafka, NATS)
• Inference and model-routing infrastructure optimized for cost and latency (vLLM, Ray, OpenAI and Anthropic APIs)
• Persistent memory and advanced retrieval: Postgres, Redis, pgvector, Neo4j, Graph RAG, hybrid search
• Tool and enterprise integrations via MCP and APIs (Salesforce, SAP, ServiceNow, Oracle, Workday)
• Human-in-the-loop controls: escalation, approvals, confidence thresholds and override
• Evaluation, monitoring and audit logging for every agent decision (LangSmith, OpenTelemetry, Prometheus, Grafana)
• Deployment on Docker, Kubernetes and Terraform across AWS, Azure or GCP

REQUIREMENTS
• Proven experience building and operating autonomous or multi-agent systems in real production
• Ability to own the full system: architecture, infrastructure, deployment, security, evaluation and reliability
• Strong distributed systems skills: idempotency, retries, replay, backpressure, fault tolerance
• Security-first approach: prompt injection, tool abuse, memory poisoning and access control
• Deep async Python (asyncio, concurrency, queues)
• Experience setting and meeting reliability targets (SLOs) for latency, uptime and cost
• Production integration experience with at least two of Salesforce, SAP, ServiceNow, Oracle or Workday
• Able to work independently without a technical lead

PLEASE DO NOT BID IF
Your main experience is chatbot wrappers, simple RAG apps, Streamlit demos, no-code workflows or prompt engineering only.

PROJECT STAGES
1. Paid 90-minute live architecture review
2. Paid 3–4 hour live build of a working multi-agent system (it must run)
3. Review call on a production system you have built
4. Live security and reliability review of your design
5. Ongoing long-term work

HOW TO BID
Bids without these will not be considered:
1. Your GitHub and LinkedIn links
2. The most impressive autonomous system you have shipped, your role, and what runs in production today
3. The hardest production failure you fixed and how you prevented it from happening again
4. Your hourly rate and weekly availability

Start your bid with the word "DETERMINISTIC" so we know you read the full description.

Start your bid with the word "DETERMINISTIC" so we know you read the full description.

Skills: Cloud Computing, Machine Learning (ML), Amazon Web Services, Hadoop, Node.js, AI Development, AI Agents, AI Automation

Senior DevOps Engineer Needed – AWS, EKS, Kubernetes & Terraform

I am looking for an experienced DevOps Engineer to troubleshoot and resolve a complex issue in our AWS cloud infrastructure.

Required Skills:
- AWS (EKS, EC2, Lambda, IAM, VPC)
- Kubernetes & Docker
- Terraform & Ansible
- Grafana Monitoring & Troubleshooting
- CI/CD Pipelines
- Linux, Networking & Infrastructure Debugging

Requirements:

- Strong hands-on experience with production AWS environments.
- Expertise in identifying root causes of complex infrastructure issues.
- Ability to troubleshoot and implement reliable solutions.
- Available for immediate support and technical discussions.

To Apply:

Please share your relevant experience, availability, and examples of complex DevOps issues you've resolved.

Note: We need an expert problem solver, not someone with only basic DevOps knowledge.

Hello ,
Terraform CICD check script

Need to implement CICD check - Should we add a check like this :

- step:
type: Run
name: Checkov Scan
identifier: checkov_scan
spec:
shell: Bash
command: |
set -e
checkov -d . --framework terraform

We’re building a library of ready-to-run test environments from popular open-source web apps, such as Grafana, Gitea and WordPress. For each app, you’ll get it running in Docker, explore it while recording its traffic, and package everything into a bundle we can start with one command. We give you a step-by-step guide for every part.

For each app, you’ll:

1. Set up: run the app in Docker Compose at the exact version we specify, finish the first-run setup, and create the users listed in the guide (for example, an admin and a regular user).
2. Explore: with Burp Suite recording traffic, log in as each user and go through every page and feature, so every request the app makes is captured. We’ll show you how to use Burp, and no prior experience is needed.
3. Package: turn the working app into a self-contained Docker bundle that starts with everything already in place: database, users and settings. Nothing should need to be set up by hand after docker compose up.
4. Deliver: send us the bundle, which includes:
• the Compose file, pinned to the exact version
• the database and app data
• a short README covering the version, the user logins and how to start it
• the exported Burp history from your walkthrough

You’ll do well if you:
• are comfortable with Docker and Docker Compose (volumes, environment variables, networks)
• have some Python or JavaScript experience
• are patient and thorough, and follow written steps closely

Nice to have: Burp Suite, Postman or QA testing experience.

How it works:
• You’ll need a computer with at least 16 GB RAM that runs Docker (Linux, macOS, or Windows with WSL2).
• Each app has an agreed hour estimate before you start. Tell us early if it looks like it will run over.
• Everything runs locally on your machine.
• There’s a short NDA, and everyone starts with one paid pilot app.

To show you’ve read this far, start your proposal with the name of the last Docker image you pulled.

I’m spinning up a UPT-based initiative that needs hands-on IoT and artificial-intelligence engineering talent. The first milestone centres on a smart-home environment where multiple sensors and devices stream data that must be captured, analysed and displayed in real time. I already have basic hardware prototypes on the bench; what I need now is an end-to-end solution that reliably moves data from the edge to the cloud, applies lightweight AI for instant insights, and returns actionable notifications with minimal latency.

You should be comfortable designing embedded firmware (ESP32/Arduino-class boards or similar), setting up secure over-the-air updates, and wiring the data pipeline—MQTT or another broker, a fast time-series database, and a responsive dashboard (Grafana, React, or your preferred framework). On the AI side, expect to build or integrate models that can spot anomalies or usage patterns on the fly; Python, TensorFlow Lite, or Edge Impulse are all fair game as long as inference happens quickly.

Acceptance criteria for this phase:
• Architecture diagram covering device, gateway, cloud and mobile layers
• Working firmware that pushes sensor data every second with <2 % packet loss in a 24-hour test
• Server-side service that stores, visualises and flags anomalies within 3 s of occurrence
• Source code in a clean repo plus setup scripts and README so I can reproduce the stack on a fresh machine

Clear, well-commented code and concise documentation will unlock the next set of UPT projects waiting in the pipeline. If this sounds like your wheelhouse, let’s talk deliverables and timeline.

Skills: Python, Electronics, Cloud Computing, PCB Layout, Arduino, MQTT, Embedded Systems, Firmware Development

We’re looking for an experienced DevOps Engineer to help us build, automate, and maintain reliable cloud infrastructure.
You’ll work closely with our dev team to improve deployment speed, system reliability, and security.

What you’ll do:

Design, build, and maintain cloud infrastructure on any cloud platform preferablly AWS, GCP or Azure
Set up and optimize CI/CD pipelines
Containerize applications with Docker and manage deployments on Kubernetes
Write and maintain Infrastructure as Code using Terraform (or CloudFormation)
Implement monitoring, logging, and alerting with tools like Prometheus, Grafana, Datadog, or CloudWatch
Improve security practices, including IAM policies, secrets management, and network configuration
3+ years of hands-on DevOps or SRE experience
Strong experience with Cloud and core services (EC2, VPC, RDS, S3, IAM)
Scripting in Bash and Python (or Go)
Comfortable with Linux system administration.

Nice to have:

Relevant certifications (AWS Solutions Architect, CKA, Terraform Associate, etc..)
Experience with Helm, ArgoCD, or other GitOps tools
Background in cost optimization for cloud environments
Experience with compliance standards (SOC 2, HIPAA, GDPR)

Remote · Freelance · Part-time or Project-based / Consulting

We are looking for a senior engineer with deep Slurm experience to support real-world, large-scale HPC and AI/ML cluster environments. This is not a “set up a small test cluster” role. You will work with Hossted.com’s open-source consulting practice on enterprise cases involving hundreds of nodes and multiple clusters. This includes joining client calls, answering technical questions with confidence, and giving practical, production-ready recommendations. Immediate availability is a big plus, as onboarding is starting now.

What You’ll Work On:
· Joining technical calls with prospective and existing clients as the Slurm subject-matter expert.
· Advising on architecture and best practices for large, multi-cluster Slurm deployments (hundreds of nodes).
· Troubleshooting scheduler issues: job failures, pending/stuck jobs, node state problems, and slurmctld/slurmd/slurmdbd errors.
· Designing and tuning scheduling policies: partitions, QoS, fairshare, priorities, preemption, and backfill.
· Managing resources and accounting: cgroups, GPU/GRES scheduling, limits, and slurmdbd with MariaDB/MySQL.
· Supporting upgrades, migrations, and high-availability setups (backup controllers, federation, multi-cluster).
· Integrating Slurm with shared storage, authentication (Munge, LDAP/SSO), monitoring (Prometheus, Grafana), and automation tools (Ansible, Terraform).

Requirements:
· Proven hands-on experience operating Slurm in production on large clusters (100+ nodes).
· Deep knowledge of Slurm configuration, scheduling, and accounting.
· Experience with multi-cluster or federated environments.
· Experience with GPU scheduling and resource management (GRES, cgroups).
· Solid Linux, networking, and shared-storage skills (NFS, Lustre, BeeGFS, or similar).
· Experience with automation and monitoring in HPC environments.
· Strong debugging and root-cause analysis skills.
· Excellent spoken and written English. You will speak directly with clients and must be confident and professional on calls.

About Hossted:
Hossted is a U.S.-based company working with 300+ open-source technologies. We help companies solve complex technical issues through expert consulting: fast, practical, and hands-on. This role is part of our open-source expert network, supporting clients who run Slurm as a critical part of their compute infrastructure.

Best Fit:
A senior HPC/Slurm engineer who has run large production clusters, communicates clearly with clients, and can make a strong technical impression in client-facing conversations.

To Apply:
Please include a brief note describing a Slurm environment you have managed or supported: cluster size (nodes/GPUs), number of clusters, workload type, and the most complex issue you resolved. Also let us know your availability for a call in early November.

We are Gulf Future Business (GFB Solutions), a technology company in Bahrain. We need an experienced HPC / AI infrastructure engineer to deliver the complete software platform on a single on-premises AI server for a university in Bahrain.

HARDWARE (already supplied)
- HPE ProLiant DL385 Gen11, 2U
- 2 x NVIDIA RTX PRO 6000 Blackwell 96GB (PCIe), 2 free GPU slots
- 2 x AMD EPYC 9274F (48 cores), 256GB DDR5 ECC (512GB upgrade under review)
- 7 x 3.84TB NVMe, 2 x 10GbE, HPE iLO

SCOPE (full scope, end to end)
1. Ubuntu Server 24.04 LTS, RAID/ZFS layout, CIS hardening
2. NVIDIA drivers, CUDA, cuDNN, NVIDIA Container Toolkit, Docker, Docker Compose
3. JupyterHub with containerised per-user environments (Python, PyTorch, TensorFlow)
4. VS Code Server and Open WebUI with local LLMs (Ollama / vLLM)
5. Microsoft Entra ID SSO with roles: Students, Faculty, Researchers, Administrators
6. GPU sharing for 30-50 concurrent users: MIG, per-user/role quotas, priorities, idle culling
7. Optional: Slurm with GPU scheduling, QoS and fair-share (priced separately)
8. Storage: user/project quotas, shared folders, snapshots and external backup
9. Monitoring and security: Prometheus, Grafana, NVIDIA DCGM, syslog/audit logging, Microsoft Defender onboarding, Fail2ban
10. Load testing, UAT support, admin training, full documentation and 30 days post go-live support

WHAT TO INCLUDE IN YOUR PROPOSAL
- Fixed price for the full scope, with Slurm priced separately
- Optional annual support price
- Estimated days, and how much is remote vs on-site in Bahrain
- 1-2 similar projects you have delivered (GPU servers, Slurm, JupyterHub)
- Your recommendation on GPU sharing, RAID and whether Slurm is needed

Work is mostly remote, with some on-site days in Bahrain for setup and handover. A detailed RFP will be shared with shortlisted candidates. Proposals by 28 October 2026.

DevOps Engineer

Company: Allneeda Group
Location: Remote
Employment Type: Full-time
Experience: 4+ years in DevOps / Cloud / Infrastructure roles
Salary Range: 400–700 USD per month
Reports To: [Engineering Manager / Head of Engineering]
About the Role

We are looking for a skilled and hands-on DevOps Engineer to build, automate, and maintain the infrastructure that powers our applications. You will work closely with development teams to design reliable CI/CD pipelines, manage containerized workloads on Kubernetes, and ensure our systems are secure, observable, and highly available across cloud environments.

Strong practical experience with Docker, Kubernetes, CI/CD pipelines, Grafana-based monitoring, and centralized logging is mandatory for this role.

Key Responsibilities

Design, build, and maintain CI/CD pipelines using Jenkins, GitHub Actions, and GitLab CI/CD to enable fast, reliable, and automated releases.
Containerize applications with Docker and Docker Compose, and maintain optimized, secure container images.
Deploy, manage, and scale workloads on Kubernetes clusters, including Deployments, Services, Ingress, ConfigMaps, Secrets, and Helm charts.
Provision and manage cloud infrastructure on AWS, Azure, and DigitalOcean using Terraform, and automate configuration with Ansible.
Configure and manage Nginx and Traefik as web servers, reverse proxies, and load balancers, including SSL/TLS certificate management.
Set up and maintain monitoring and alerting with Prometheus and Grafana, building dashboards that give clear visibility into system and application health.
Implement centralized logging using the ELK Stack (Elasticsearch, Logstash, Kibana) and Loki for troubleshooting and analysis.
Manage Node.js application processes with PM2 and handle dependency management with npm and pnpm.
Administer, back up, and tune PostgreSQL, MongoDB, and Redis, and support RabbitMQ message broker setups.
Enforce Git branching strategies, code review workflows, and repository management across GitHub and GitLab.
Troubleshoot production incidents, perform root cause analysis, and drive improvements in uptime, performance, and cost efficiency.
Apply security best practices across infrastructure, including access control, secrets management, network policies, and vulnerability scanning.
Maintain clear documentation of infrastructure, runbooks, and deployment processes.
Must-Have Skills

Docker: Strong hands-on experience building, optimizing, and debugging containers.
Kubernetes: Deploying and operating production workloads, cluster management, and troubleshooting.
CI/CD: Designing and maintaining end-to-end automated build, test, and deployment pipelines.
Grafana: Creating dashboards, panels, and alerts for infrastructure and application monitoring.
Logging: Setting up and managing centralized logging with the ELK Stack and Loki, including log aggregation, parsing, retention, and search for troubleshooting.
Technical Skills & Tools

Candidates should have working knowledge of the following technology stack:

Version Control: Git, GitHub, GitLab
CI/CD: Jenkins, GitHub Actions, GitLab CI/CD
Containers: Docker, Docker Compose
Container Orchestration: Kubernetes
Cloud Platforms: AWS, Azure, DigitalOcean
Web Server / Reverse Proxy: Nginx, Traefik
Infrastructure as Code: Terraform, Ansible
Monitoring: Prometheus, Grafana
Logging: ELK Stack, Loki
Package Management: npm, pnpm
Process Management: PM2
Databases / Cache: PostgreSQL, MongoDB, Redis
Message Broker: RabbitMQ
Qualifications

Bachelor’s degree in Computer Science, Information Technology, or a related field (or equivalent practical experience).
4+ years of experience in DevOps, Site Reliability Engineering, or cloud infrastructure roles.
Solid understanding of Linux system administration, shell scripting (Bash), and networking fundamentals (DNS, TCP/IP, HTTP/S, load balancing).
Proven experience running containerized applications in production environments.
Scripting ability in Bash, Python, or a similar language for automation.
Good to Have

Certifications such as AWS Certified DevOps Engineer, Certified Kubernetes Administrator (CKA), or Microsoft Azure Administrator.
Experience with Helm, ArgoCD, or other GitOps tools.
Familiarity with secrets management tools such as HashiCorp Vault or AWS Secrets Manager.
Exposure to DevSecOps practices and tools like Trivy, SonarQube, or Snyk.

My production box is a high-traffic Linux server that keeps thousands of TCP connections open at any given moment. It is already running Nginx, but connection spikes are starting to expose bottlenecks and a few security gaps. I need a DevOps specialist who can step in and deliver three things in one engagement: noticeable performance tuning, solid security hardening, and smarter resource management.

Here is what I have in place:
• Ubuntu-based host on a dedicated machine
• Nginx handling both HTTP and long-lived TCP streams via stream{} blocks
• Basic monitoring with top/iostat and Nginx stub_status

What I need from you:
1. Tune the kernel (sysctl, ulimits, epoll, TCP backlog, etc.) and Nginx worker settings so the server continues to serve traffic smoothly even when connection counts jump.
2. Lock down obvious attack surfaces—TLS configuration, headers, fail2ban, firewall rules, and any Nginx-specific best practices—without sacrificing throughput.
3. Rebalance CPU, memory, and disk I/O so the machine stays under sensible thresholds during load tests and can self-recover if one resource saturates.

Deliverables (all version-controlled or clearly documented):
• Updated configuration files (sysctl.conf, limits.conf, nginx.conf)
• A before/after benchmark report showing latency, throughput, and resource usage improvements
• Security hardening checklist with each item marked off and verified
• A lightweight monitoring or alerting script/dashboard (Prometheus, Grafana, or similar) that visualizes key metrics

Acceptance criteria: all changes must pass a 30-minute stress test at 1.5× current peak traffic with no dropped connections and average latency no worse than present baseline.

If that sounds like your wheelhouse, tell me which specific tools you would reach for first and how quickly you can begin.

Skills: Linux, Web Security, Apache, Nginx, DevOps, Network Security, Performance Tuning, System Administration

WE’RE HIRING | DevOps Trainer | Part-Time

Build skills. Share expertise. Shape the next generation of DevOps professionals.Are you a seasoned DevOps professional who enjoys turning real-world technical experience into practical learning?
Workoopolis is looking for an experienced DevOps Trainer who can bridge the gap between industry practices and hands-on learning.
If you have strong technical expertise, real-world project experience, and a passion for mentoring aspiring professionals, this opportunity is for you!

🎯 What You’ll Do
🔹 Deliver engaging, practical DevOps training sessions.
🔹 Train learners on DevOps tools, workflows, cloud technologies, and CI/CD practices.
🔹 Incorporate hands-on exercises, real-world projects, and industry use cases.
🔹 Develop structured training content tailored to learner needs.
🔹 Mentor learners and help them build job-ready technical skills.

🛠️ What We’re Looking For
✅ 7+ years of hands-on DevOps experience — mandatory.
✅ Strong knowledge of DevOps tools, cloud platforms, automation, and CI/CD pipelines.
✅ Prior teaching or technical training experience is essential.
✅ Excellent communication, presentation, and mentoring skills.
✅ Ability to simplify complex technical concepts and deliver effective online sessions.

💼 Engagement: Part-Time / Freelance
📌 Experience: Minimum 7+ Years (Mandatory)

📩 Ready to turn your DevOps expertise into someone else’s career advantage?Share your updated resume and a brief professional profile at:

PROJECT
AI-Powered Network Intrusion Detection System (NIDS)
Project Objective

Build a machine learning-based NIDS that classifies network traffic as normal or malicious in real time, detects attack types (DDoS, port scan, brute force, SQL injection traffic), generates alerts, and produces a visual dashboard — mimicking what enterprise SOC tools like Darktrace and Securonix do.

Project Details Table
Attribute Details
Full Title AI-Powered Network Intrusion Detection System using Machine Learning & Python
Domain Network Security + Artificial Intelligence + SOC Operations
Difficulty (Intermediate–Advanced)
Duration 10–12 weeks
Team Size 1–2 students
Total Cost ₹0 (fully open-source)
Publication Scope GitHub + Research Paper (IJERA / IRJET journals)
Resume Line “Built an ML-based NIDS achieving 97.3% accuracy on KDD Cup 99 dataset; deployed real-time alert dashboard using Streamlit and Scikit-learn”
Tools & Technologies
Category Tools
Language Python 3.x
ML Libraries Scikit-learn, XGBoost, TensorFlow/Keras
Data Processing Pandas, NumPy, Matplotlib, Seaborn
Network Tools Wireshark, Scapy, tcpdump
Dashboard Streamlit / Grafana
Dataset NSL-KDD / CICIDS 2017 / KDD Cup 99 (all free)
Version Control GitHub
Environment Kali Linux VM / Ubuntu
Week-by-Week Execution Plan
Week Task Deliverable
Week 1–2 Dataset selection, EDA, data cleaning, feature engineering Cleaned dataset + EDA report
Week 3–4 Train baseline ML models (Random Forest, SVM, KNN) Model comparison table with accuracy scores
Week 5–6 Implement Deep Learning model (LSTM / CNN for traffic sequences) DL model with improved accuracy
Week 7–8 Build real-time packet capture module using Scapy Live traffic classifier script
Week 9–10 Build Streamlit dashboard with live alerts, traffic graphs, attack logs Working interactive dashboard
Week 11–12 Testing, documentation, GitHub README, write research paper Final project + publishable paper
Deliverables Checklist
Deliverable Format
Trained ML/DL models with accuracy > 95% .pkl / .h5 files
Real-time network traffic classifier Python script
Interactive SOC-style dashboard Streamlit web app
Comparison report — all models vs baselines PDF report
Published GitHub repository with documentation GitHub link
Research paper submitted to journal PDF / DOI link

Skills: Python, Linux, Data Processing, Machine Learning (ML), Network Administration, Deep Learning, Network Security, Pandas

We are looking for an experienced Senior Software Engineer to support our existing development team on a part-time, long-term basis.

We have an established SaaS application already in production and a team handling day-to-day development. We need an additional experienced engineer who can help us solve challenging technical problems, improve our architecture, and occasionally contribute to feature development.

This is not a project to build an application from scratch. We are looking for someone who can quickly understand an existing codebase, collaborate with our developers, and provide practical technical solutions.

Tech Stack

Backend: Node.js, TypeScript, Go (Golang)

Frontend: React, Next.js

Databases: PostgreSQL, MongoDB

Caching & Messaging: Redis, Kafka

Infrastructure: Docker, AWS, Kubernetes, CI/CD

Monitoring: Grafana, Prometheus

You don't need to be an expert in every technology, but strong backend experience and comfort working across the stack are important.

Responsibilities

Help our team troubleshoot complex backend and production issues.

Review existing architecture and recommend practical improvements.

Optimize PostgreSQL/MongoDB queries, Redis caching, and API performance.

Assist with development and maintenance of Node.js/TypeScript and Go services.

Occasionally implement or improve features across the frontend and backend.

Help improve Docker configurations, deployments, CI/CD pipelines, and application monitoring.

Review code and provide technical guidance to other developers.

Identify potential scalability, reliability, and performance problems.

What We're Looking For

5+ years of professional software development experience.

Strong experience with Node.js, TypeScript, and backend architecture.

Solid understanding of PostgreSQL, MongoDB, and Redis.

Experience with React/Next.js applications.

Familiarity with Docker, Linux, cloud infrastructure, and DevOps practices.

Experience debugging and improving existing production systems.

Ability to work independently and communicate effectively with an existing team.

Experience with Go (Golang), distributed systems, Kafka, Kubernetes, or high-traffic applications is a plus.

Engagement Details

5–8 hours per week, maximum 10 hours

Long-term collaboration, ideally 6+ months

Fully remote

Flexible working hours, primarily asynchronous

Occasional technical meetings with the team

No regular on-call or 24/7 support responsibilities

Focus on supporting and improving an existing product rather than leading a new development project

We're looking for a reliable, experienced engineer who can become a trusted technical contributor to our team over the long term.

When applying, please share examples of how you've helped an existing team improve an application's performance, reliability, architecture, or development workflow.

Project Overview

I am looking for an experienced DevOps Engineer to provide ongoing job support for an initial period of 3 months, with the possibility of extension.

The ideal candidate must have strong practical experience with Docker Swarm, Docker, Portainer, Ansible, Prometheus, Grafana, Traefik, system migrations, and software upgrades.

I need someone who can provide technical guidance, assist with troubleshooting, explain solutions clearly, and document technical activities, configurations, and resolutions.

Required Technical Skills

1. Docker and Docker Swarm, including cluster management, service deployment, networking, stack management, troubleshooting, and high availability.
2. Portainer for managing Docker environments, stacks, services, and container operations.
3. Ansible for configuration management, automation, provisioning, and repeatable deployments.
4. Prometheus and Grafana for monitoring, metrics collection, dashboards, alerting, and troubleshooting.
5. Traefik for reverse proxy configuration, routing, TLS certificates, and service discovery.
6. Software upgrades, version compatibility checks, upgrade planning, backups, rollback procedures, and post upgrade validation.
7. System and application migrations, including planning, execution, validation, and recovery procedures.
8. Linux administration, log analysis, networking, and general DevOps troubleshooting.

Engagement Details

Duration: 3 months initially, with the possibility of extension.

Frequency: 3 sessions per week.

Session length: 1 hour per session.

Total estimated time: 36 hours over 12 weeks.

Total budget: USD 300 monthly for the initial 3 month engagement.

Availability: My working hours are between 10:00 AM and 7:00 PM Atlantic Time. All sessions must be scheduled within this window, subject to mutual agreement.

Expected Deliverables

1. Three one hour technical support sessions per week.
2. Practical guidance and troubleshooting support for relevant DevOps tasks.
3. Assistance with Docker Swarm, Portainer, Ansible, Prometheus, Grafana, and Traefik configurations.
4. Technical guidance on system migrations, software upgrades, and deployment changes.
5. Documentation of issues, root causes, resolutions, and changes made.
6. Step by step technical procedures and operational runbooks where applicable.
7. Upgrade and migration documentation covering prerequisites, dependencies, backups, validation, and rollback procedures.
8. Action items and recommendations following each session.
9. Monthly progress summaries and final handover documentation.

Security and Operational Expectations

The freelancer must follow secure engineering practices, use least privilege access, protect credentials and sensitive information, and obtain approval before implementing infrastructure changes.

Backups, rollback plans, and post change validation must be considered before significant upgrades or migrations. Credentials must not be hardcoded or shared insecurely.

Application Questions

Please answer the following questions in your proposal. Generic answers will not be sufficient. Provide specific examples from environments you have actually managed or supported, while excluding confidential client information.

1. Docker Swarm experience

Describe your hands on experience with Docker Swarm. Have you managed manager and worker nodes, deployed stacks, configured overlay networks, managed secrets, or troubleshot failed services? Describe a challenging issue you resolved and how you resolved it.

2. Docker Swarm migrations

Have you migrated applications, services, or workloads into or out of Docker Swarm, or between Swarm clusters? Describe the source and target environments, your migration approach, how you handled persistent volumes and application data, and how you validated the migration.

3. Portainer management

What experience do you have managing Docker Swarm environments through Portainer? Explain how you manage stacks, troubleshoot deployment failures, and maintain environment access securely.

4. Ansible automation

Describe an Ansible automation project you have implemented. What did your playbooks automate, how did you manage variables and secrets, and how did you make the tasks repeatable and safe to run?

5. Prometheus and Grafana

Describe a monitoring environment you have configured using Prometheus and Grafana. What metrics did you collect, which exporters or integrations did you use, and how did you configure dashboards and alerts?

6. Traefik configuration

Explain your experience configuring Traefik with Docker or Docker Swarm. How have you handled routing, service discovery, TLS certificates, and troubleshooting inaccessible applications or failed routes?

7. Software upgrades

Describe a significant software or infrastructure upgrade you have performed. How did you assess compatibility, prepare backups, plan the maintenance window, validate the upgrade, and recover if something went wrong?

8. System migration and troubleshooting

Describe a real world migration or complex troubleshooting incident you have handled. What was the problem, what steps did you take, what risks did you consider, and what was the final outcome?

9. Documentation

Can you provide clear technical documentation after each support session, including issues discussed, troubleshooting steps, root causes, solutions, commands or configuration changes where appropriate, and follow up actions?

10. Availability and budget

Can you commit to three one hour sessions per week for an initial three month period, scheduled between 10:00 AM and 7:00 PM Atlantic Time, for a total budget of USD 300? Please indicate your preferred recurring session times.

Ideal Candidate

The successful candidate should have demonstrable production or substantial hands on experience, strong troubleshooting skills, a structured approach to migrations and upgrades, and the ability to explain technical decisions clearly.

I value practical experience, reliability, clear documentation, and secure operational practices.

Please answer all application questions directly and include relevant examples of your work.

The engagement may be extended based on performance and mutual agreement.

Job Description:
We are seeking a highly skilled and proactive Senior DevOps Engineer to join our team. You will be responsible for designing, implementing, and maintaining robust CI/CD pipelines, managing cloud infrastructure across multiple providers, and ensuring high availability and security.
The ideal candidate is a automation-first mindset engineer who is comfortable working with containerized microservices and has experience deploying AI models in serverless environments.

Key Responsibilities:
1. CI/CD Management: Design, build, and maintain efficient CI/CD pipelines using Jenkins, GitLab CI, CircleCI, or GitHub Actions.
2. Containerization & Orchestration: Manage containerized applications using Docker and orchestrate them using Kubernetes (EKS, AKS, GKE) .
3. Infrastructure as Code (IaC): Implement and manage infrastructure using Terraform, AWS CloudFormation, and Ansible.
4. Cloud Operations: Architect and maintain solutions across AWS, Azure, and Google Cloud Platform.
5. Monitoring & Observability: Set up comprehensive monitoring and logging using Prometheus, Grafana, ELK Stack, or Datadog.
6. Monitoring & Observability: Set up comprehensive monitoring and logging using Prometheus, Grafana, ELK Stack, or Datadog.
7. Security (DevSecOps): Integrate security into the DevOps lifecycle, including vulnerability scanning and secrets management.
8. Scripting & Automation: Develop automation scripts using Bash, Python, and PowerShell to eliminate repetitive tasks.
9. Deployment Strategies: Implement Blue/Green and Canary deployments to ensure zero-downtime releases.
10. AI/ML Deployment: Deploy AI models and utilize cloud-provided models within serverless cloud infrastructure.
11. Collaboration: Work closely with Development and QA teams within Agile/Scrum frameworks to ensure smooth releases.


Required Skills & Qualifications:

1. Experience: 5+ years of experience in DevOps, SRE, or Cloud Engineering roles.
2. Cloud Mastery: Deep hands-on experience with at least two of the major cloud providers (AWS, Azure, GCP).
3. Orchestration: Strong expertise in Kubernetes cluster management and service mesh technologies like Istio or Linkerd.
4. Configuration Management: Proficiency in Ansible, Puppet, or Chef.
5. Version Control: Expert knowledge of Git, GitHub, GitLab, and Bitbucket.
6. Architecture: Experience in Disaster Recovery planning and designing High Availability architectures.
7. Soft Skills: Excellent communication skills and the ability to work independently in a fast-paced environment.

Description

We run a production platform serving a growing user base and need a senior DevOps/SRE engineer to own our infrastructure, improve reliability, and cut cloud costs. This is an infrastructure-only role with no application feature work.

What you’ll work on

Migrate our workloads to Kubernetes (GKE) with Helm charts and GitOps deployments (ArgoCD)
Build and maintain infrastructure as code with Terraform and Ansible
Redesign CI/CD pipelines (GitHub Actions or Jenkins) with automated testing, security scanning, and rollbacks
Set up observability: Prometheus, Grafana, Loki, alerting, and on-call runbooks
Harden security: IAM, secrets management (Vault), network policies, vulnerability scanning
Define SLOs, run incident response, and write post-mortems
Reduce cloud spend through right-sizing, autoscaling, and cost monitoring

Required experience

Experienced in DevOps, SRE, or infrastructure engineering
Strong hands-on Kubernetes in production (not just Docker)
GCP experience, with AWS a plus
Terraform, Ansible, and Linux administration
Scripting in Bash and Python or Go
Monitoring and incident management experience
Clear written English and availability for on-call overlap with US hours

Nice to have
Service mesh (Istio), Datadog or New Relic, PostgreSQL administration, SOC 2 or ISO 27001 exposure, chaos engineering.

To apply, please include

Two infrastructure projects you’ve delivered, with scale (traffic, clusters, uptime)
How you would approach a zero-downtime migration to Kubernetes
Your availability and expected start date

Screening questions

Describe a production outage you handled. What was the root cause and what did you change afterward?
How do you structure Terraform for multiple environments and teams?
What observability stack have you run, and which alerts do you consider essential?

🌍 Candidate Locations: UAE & India Only
💼 Position: Senior AI Architect / LLM Inference & GPU Infrastructure Architect
💰 Monthly Salary: USD 4,000–5,000 (Depending on Experience & Expertise)
📅 Engagement: Full-Time | Dedicated | Long-Term Contract
🎯 Experience: 8+ Years Preferred
⏳ Joining: Immediate / Short Notice Preferred


🔥 About the Opportunity

looking for highly experienced, hands-on Senior AI Architects based in the UAE or India for a full-time, dedicated, long-term engagement supporting enterprise AI and large-scale LLM inference infrastructure.

We are NOT looking for candidates who only develop GenAI applications, integrate OpenAI APIs, or have theoretical AI architecture knowledge.

We need professionals who have actually deployed, optimized, scaled, and managed production LLMs on NVIDIA GPU clusters and Kubernetes infrastructure.

🔹 1. LLM Serving & Inference Engines

✅ Strong hands-on expertise in vLLM, Hugging Face TGI, TensorRT-LLM, and production LLM model serving.

✅ Deep understanding of continuous batching, chunked prefill, PagedAttention, KV cache management, and inference optimization.

✅ Experience optimizing Time-to-First-Token (TTFT), Inter-Token Latency (ITL), throughput, GPU utilization, and cost per token.

🔹 2. Distributed Inference & Multi-GPU Architecture

✅ Experience deploying 70B+ parameter LLMs on NVIDIA H100, H200, A100, or equivalent GPUs.

✅ Expertise in Tensor Parallelism (TP), Pipeline Parallelism (PP), Context Parallelism, and distributed model execution.

✅ Knowledge of NVLink, NVSwitch, InfiniBand, RoCE/RDMA, and GPU communication optimization.

🔹 3. Quantization & GPU Performance Optimization

✅ Practical expertise in FP8, INT4, AWQ, GPTQ, and hardware-aware quantization.

✅ Experience implementing speculative decoding, Medusa, EAGLE, and inference acceleration.

✅ Knowledge of Triton kernels, FlashAttention, FlashInfer, CUDA profiling, and GPU performance tuning.

🔹 4. Bare-Metal Kubernetes & NVIDIA GPU Infrastructure

✅ Hands-on experience deploying and managing bare-metal Kubernetes GPU clusters.

✅ Expertise in NVIDIA GPU Operator, Device Plugin, MIG, GPU scheduling, and resource isolation.

✅ Experience with GPU fault tolerance, autoscaling, high availability, XID errors, and cluster troubleshooting.

✅ Knowledge of Ceph, JuiceFS, NVMe, S3-compatible storage, and model-weight caching.

🔹 5. Production Monitoring & Observability

✅ Experience with Prometheus, Grafana, NVIDIA DCGM Exporter, and OpenTelemetry.

✅ Expertise in monitoring TTFT, ITL, tokens/sec, GPU utilization, and inference performance.

✅ Knowledge of Envoy, Traefik, SSE streaming, API gateways, and GPU-aware load balancing.

🎯 Mandatory Candidate Requirements

We will prioritize candidates who can demonstrate:

Actual production deployments of LLM inference platforms using vLLM, TensorRT-LLM, or TGI.

Hands-on experience with NVIDIA GPU clusters and Kubernetes orchestration.

Proven experience optimizing LLM latency, throughput, quantization, and GPU utilization.

Ability to independently architect, configure, troubleshoot, and scale enterprise inference infrastructure.

Real project implementation evidence, architecture diagrams, configurations, or performance benchmarks.

⚠️ General AWS/DevOps/Kubernetes experience without GPU-based LLM inference expertise is NOT sufficient for this role.

💰 Compensation & Contract

💵 USD 4,000–5,000 per month, based on technical expertise and relevant production experience.

✅ Full-time, dedicated engagement
✅ Long-term contract opportunity
✅ Candidates based in UAE or India
✅ Immediate or short-notice availability preferred

📩 How to Apply

Please submit your Upwork proposal along with:

Updated CV / Resume (PDF).

Total experience and relevant GPU/LLM inference experience.

Details of 2–3 real production LLM/GPU deployments you have personally worked on.

Specific experience with vLLM, TensorRT-LLM, NVIDIA GPU Operator, and distributed inference.

Current location (UAE / India).

Expected monthly compensation (USD).

Notice period / earliest availability.

🔥 Important: Technical Screening

Shortlisted candidates will participate in a hands-on technical discussion covering model serving, multi-GPU inference, Kubernetes GPU orchestration, quantization, and performance optimization.

We are interested in architects who have built and operated real production GPU/LLM systems, not just theoretical knowledge or AI-generated solution designs.

We are looking for a Prometheus Grafana expert to customize Grafana dashboards that display servers, network devices, and storage systems in organized groups. The work includes monitoring key metrics such as CPU, memory, and storage usage across these assets and presenting them on well-structured dashboards. The ideal freelancer should be able to improve dashboard layout, organize data clearly, and ensure the dashboards are easy to read and maintain.

We are an Australian GPU cloud provider building a small bench of freelance engineers to deploy and support customer GPU environments. Work includes project-based setups and ongoing support with capped hours. We are seeking long-term partners.

Our infrastructure includes on-demand GPU instances, dedicated 8-GPU nodes and enterprise clusters with H100, H200, B200 and B300 GPUs. Customer workloads include AI training and inference. Infrastructure is in Australia, with partner capacity in the UK, Europe and the US.

Responsibilities

- Set up Ubuntu GPU servers with NVIDIA drivers, CUDA, Docker and NVIDIA Container Toolkit.
- Deploy model inference services such as vLLM, TGI or Triton behind HTTPS.
- Configure Prometheus, Grafana and DCGM Exporter monitoring and downtime alerts.
- Resolve customer access issues, GPU errors, service restarts and patching tickets.
- Turn working deployments into reusable Ansible, Terraform or script templates.
- On larger projects, support multi-node training with Slurm or Kubernetes, NCCL and InfiniBand.

Required experience

- Strong Ubuntu/Linux administration and production NVIDIA GPU troubleshooting, including driver/CUDA compatibility, nvidia-smi, DCGM and Xid errors.
- Docker GPU workloads, ML inference deployments, monitoring and alerting.
- Clear written English for direct customer communication.

Experience with PyTorch DDP/FSDP, DeepSpeed, Slurm, Kubernetes GPU Operator, InfiniBand/RoCE, or GPU cloud/HPC operations is useful.

Remote contract, hourly or per project. European and Asia-Pacific time zones are especially welcome. NDA, non-solicitation and IP assignment will be required. Shortlisted candidates will be offered a paid 2–3 hour test through Upwork: deploy a vLLM inference service with Grafana monitoring and downtime alerts on a GPU instance we provide.

Please apply through Upwork with: (1) specific GPU/ML infrastructure projects, GPU types and scale; (2) time zone and weekly availability; (3) hourly rate in USD; and (4) brief examples of relevant work. Keep all pre-contract communication and payment on Upwork.

We're looking for a skilled and reliable Backend Developer to support an ongoing enterprise software development project involving backend services, APIs, databases, data pipelines, and search-related applications.

You'll work with an existing codebase, troubleshoot technical issues, implement improvements, and collaborate remotely with US-based engineers and technical stakeholders.
We're looking for someone with strong backend fundamentals who can work independently, communicate confidently, and take ownership of assigned tasks.

Project Details
Location: India or Pakistan
Experience: 3+ years of professional backend development
Type: Remote
Duration: Ongoing, with potential for a long-term engagement
Start: As soon as available

Responsibilities
Build, maintain, and improve backend services using Node.js and TypeScript.
Develop and troubleshoot REST APIs, GraphQL services, and backend integrations.
Work with PostgreSQL, SQL queries, indexing, database design, and performance optimization.
Support ETL workflows, data ingestion, transformation, and synchronization between systems.
Handle retries, idempotency, duplicate processing, error recovery, and data reconciliation.
Investigate backend failures, database issues, and production incidents.
Work with AWS services, development environments, and deployment workflows.
Support enterprise knowledge-management, search, and data-processing applications.
Use application logs, monitoring tools, metrics, and traces to investigate issues.
Write clean, maintainable code with appropriate automated tests.
Participate in code reviews, technical discussions, and regular progress updates.
Understand existing technical approaches and suggest improvements where appropriate.
Required Skills
Strong hands-on experience with Node.js and TypeScript.
Good knowledge of PostgreSQL and SQL, including query optimization.
Experience developing and integrating REST APIs.
Familiarity with GraphQL and backend service architectures.
Practical experience with AWS.
Understanding of asynchronous processing, data consistency, and error handling.
Familiarity with Git, pull requests, testing, and CI/CD workflows.
Strong debugging and problem-solving skills.
Ability to understand existing systems and work independently.
Nice to Have
Experience with any of these technologies is a plus:
Snowflake and data engineering
OpenSearch / Elasticsearch
RAG and LLM-powered applications
Enterprise search and knowledge-management systems
Document ingestion, chunking, retrieval, or reranking
Python
Kafka or event-driven processing
Docker / Kubernetes
AWS Lambda, S3, or CloudWatch
Datadog, Splunk, OpenTelemetry, or Grafana
Distributed systems and production observability
You don't need to know every technology listed above. Strong fundamentals and the ability to learn unfamiliar systems are more important.
English Communication — Mandatory
This position requires frequent technical communication with engineers and stakeholders based in the United States.
Excellent spoken English is a strict requirement.
You must be able to:
Communicate fluently, clearly, and confidently in spoken English.
Understand conversational American English during live meetings.
Explain technical problems, implementation decisions, and trade-offs naturally.
Participate actively in technical discussions, video calls, and screen-sharing sessions.
Provide clear progress updates and communicate blockers promptly.
Ask relevant questions and discuss solutions without relying on scripted responses.
Clear pronunciation, listening comprehension, and effective communication are essential. A specific native accent is not required.
Candidates must be comfortable completing a live technical interview entirely in English.
What We're Looking For
We value developers who are reliable, responsible, proactive, and technically curious.
You should be comfortable investigating difficult problems, taking ownership of your work, receiving feedback, and suggesting better solutions rather than simply following instructions.
Good engineering judgment, consistent communication, and dependable delivery are especially important.
This position is strictly for individual freelancers who will personally perform the work.
Please DO NOT apply if you intend to delegate, outsource, subcontract, or hand over the assigned work to another person after being hired.

We are looking for an experienced Senior Java / Spring Boot Backend Developer to join our team on a remote freelance basis. You will work on production-grade backend systems, designing and developing REST APIs, improving existing applications, troubleshooting complex technical issues, and contributing to architecture and engineering decisions. The ideal candidate is a hands-on engineer who can take ownership of backend features from design through implementation, testing, deployment, and ongoing maintenance.

Responsibilities
• Design, develop, and maintain scalable backend applications using Java and Spring Boot
• Design and develop robust RESTful APIs
• Design clean and maintainable application architectures
• Work with relational and NoSQL databases and optimize database performance
• Analyze existing systems, identify technical issues, and implement practical improvements
• Debug production issues and perform root-cause analysis
• Improve application performance, reliability, scalability, and security
• Write clean, reusable, testable, and maintainable code
• Develop unit, integration, and end-to-end tests where appropriate
• Participate in code reviews and technical design discussions
• Work with Git and modern CI/CD practices
• Support containerized applications using Docker
• Collaborate with DevOps and engineering teams on deployment and production operations
• Document technical decisions, APIs, architecture, and implementation details
• Evaluate technologies and engineering approaches when required

Nice to Have Experience with one or more of:
• Spring Modulith or modular monolith architecture
• CI/CD pipelines
• Linux environment
• Nginx
• Prometheus / Grafana
• Event-driven architecture

What We're Looking For We value engineers who:
• Can understand an existing codebase quickly
• Take ownership of problems rather than waiting for detailed instructions
• Can make sound technical decisions and explain their reasoning
• Care about code quality, maintainability, performance, and reliability
• Are comfortable debugging difficult production issues
• Can communicate clearly with both technical and non-technical stakeholders
• Can work independently in a remote environment
• Are willing to research unfamiliar technologies and solve problems independently
• Understand that good engineering involves balancing simplicity, reliability, scalability, and delivery speed

We’re looking for a hands-on Rust Developer to build fast, reliable, memory-safe backend systems. You’ll design and write production Rust services, improve performance, and work closely with DevOps, QA and product teams. You’ll own your code from design through production.

Responsibilities
Design, build and maintain high-performance backend services and libraries in Rust.
Write clean, well-tested, maintainable code and take part in code reviews.
Build asynchronous, concurrent systems using Tokio and related libraries.
Design APIs and service-to-service communication using REST, gRPC and messaging (Kafka or RabbitMQ).
Work with PostgreSQL and other data stores (Redis, MongoDB), including schema design, indexing and query tuning.
Profile, benchmark and optimize services for latency, throughput and memory use.
Add logging, metrics and tracing (OpenTelemetry, Prometheus, Grafana) and help debug production incidents.
Contribute to CI/CD pipelines, containerized deployments and testing standards.
Mentor junior developers and help spread good Rust practices across the team.

Requirements
5+ years of professional backend development, including 2+ years of production Rust.
Strong command of Rust fundamentals: ownership and borrowing, lifetimes, traits, error handling and async/await.
Hands-on experience with Tokio and common crates (Serde, Axum or Actix, SQLx or Diesel).
Solid understanding of concurrency, multithreading and memory management.
Experience with PostgreSQL and at least one messaging system (Kafka or RabbitMQ).
Experience with Docker, Git and CI/CD pipelines, and comfort working on Linux.
Experience profiling and optimizing performance-critical code.
Strong communication skills and the ability to explain technical trade-offs clearly.

Preferred qualifications
Background in C or C++, Go or Java alongside Rust.
Experience with gRPC, Kubernetes, and a major cloud platform (AWS, Azure or GCP).
Experience with low-latency systems, trading or fintech platforms.
Experience with embedded systems, networking or security tooling.
Open-source contributions to Rust projects.
Familiarity with Terraform or Helm.
Experience with WebAssembly or blockchain technologies.

Job Description:

We are seeking a highly skilled and proactive Senior DevOps Engineer to join our team. You will be responsible for designing, implementing, and maintaining robust CI/CD pipelines, managing cloud infrastructure across multiple providers, and ensuring high availability and security.

The ideal candidate is a automation-first mindset engineer who is comfortable working with containerized microservices and has experience deploying AI models in serverless environments.

Key Responsibilities:

CI/CD Management: Design, build, and maintain efficient CI/CD pipelines using Jenkins, GitLab CI, CircleCI, or GitHub Actions.

Containerization & Orchestration: Manage containerized applications using Docker and orchestrate them using Kubernetes (EKS, AKS, GKE) .

Infrastructure as Code (IaC): Implement and manage infrastructure using Terraform, AWS CloudFormation, and Ansible.

Cloud Operations: Architect and maintain solutions across AWS, Azure, and Google Cloud Platform.

Monitoring & Observability: Set up comprehensive monitoring and logging using Prometheus, Grafana, ELK Stack, or Datadog.

Security (DevSecOps): Integrate security into the DevOps lifecycle, including vulnerability scanning and secrets management.

Scripting & Automation: Develop automation scripts using Bash, Python, and PowerShell to eliminate repetitive tasks.

Deployment Strategies: Implement Blue/Green and Canary deployments to ensure zero-downtime releases.

AI/ML Deployment: Deploy AI models and utilize cloud-provided models within serverless cloud infrastructure.

Collaboration: Work closely with Development and QA teams within Agile/Scrum frameworks to ensure smooth releases.

Required Skills & Qualifications:

Experience: 5+ years of experience in DevOps, SRE, or Cloud Engineering roles.

Cloud Mastery: Deep hands-on experience with at least two of the major cloud providers (AWS, Azure, GCP).

Orchestration: Strong expertise in Kubernetes cluster management and service mesh technologies like Istio or Linkerd.

Configuration Management: Proficiency in Ansible, Puppet, or Chef.

Version Control: Expert knowledge of Git, GitHub, GitLab, and Bitbucket.

Architecture: Experience in Disaster Recovery planning and designing High Availability architectures.

Soft Skills: Excellent communication skills and the ability to work independently in a fast-paced environment.

Für einen Kunden suchen wir einen erfahrenen Freelancer, der Apache-Kafka-Cluster auf Red Hat OpenShift (Strimzi / AMQ Streams) betreut und ausbaut. Das Team arbeitet auf Deutsch, daher ist fließendes Deutsch Pflicht.

Deine Aufgaben:
- Kafka auf OpenShift betreiben und skalieren
- Topics, Partitionen und Replikation entwerfen, Kafka Connect, Schema Registry und MirrorMaker aufsetzen
- Tuning, Fehlersuche und Überwachung mit Prometheus und Grafana
- Cluster mit TLS, SASL und ACLs absichern
- Deployments mit Argo CD, Helm und Operatoren automatisieren
- die Entwicklungsteams beraten

Du hast mehrere Jahre Kafka in Produktion hinter dir und gute OpenShift- oder Kubernetes-Kenntnisse. Start so bald wie möglich, geplant für etwa sechs Monate.

English version:
For a client we are looking for an experienced freelancer to run and extend Apache Kafka clusters on Red Hat OpenShift (Strimzi / AMQ Streams). The team works in German, so fluent German is required.

Your tasks:
- operate and scale Kafka on OpenShift
- design topics, partitions and replication, set up Kafka Connect, Schema Registry and MirrorMaker
- tuning, troubleshooting and monitoring with Prometheus and Grafana
- secure clusters with TLS, SASL and ACLs
- automate deployments with Argo CD, Helm and operators
- advise the development teams

You have several years of production Kafka experience and good OpenShift or Kubernetes skills. Start as soon as possible, planned for about six months.

SRE & AWS DevOps Engineer – Magento / Adobe CommerceJob Overview
We are looking for an experienced Site Reliability Engineer (SRE) / AWS DevOps Engineer to manage, optimize, secure, and maintain our Magento 2 / Adobe Commerce infrastructure hosted on AWS. The ideal candidate will have strong expertise in AWS cloud infrastructure, CI/CD automation, Linux administration, performance optimization, monitoring, and production incident management.
The role involves ensuring high availability, scalability, security, and performance of Magento e-commerce applications across development, staging, and production environments.
Key Responsibilities1. AWS Infrastructure Management
Design, deploy, and maintain AWS infrastructure for Magento applications.
Manage EC2, VPC, IAM, S3, RDS, ElastiCache, Application Load Balancer, Route 53, CloudWatch, and Auto Scaling.
Configure secure networking, load balancing, high availability, and disaster recovery.
Manage infrastructure provisioning and configuration using Terraform and Ansible.
Implement backup, restore, and disaster recovery procedures.
2. Magento 2 / Adobe Commerce Operations
Deploy and maintain Magento 2 applications across development, staging, and production.
Optimize PHP-FPM, Nginx, MySQL/Aurora, Redis, OpenSearch/Elasticsearch, and Varnish.
Troubleshoot Magento performance issues, HTTP 500/502/503 errors, slow queries, cache problems, and resource exhaustion.
Manage cron jobs, indexers, message queues, static content deployment, and production maintenance activities.
Support Magento upgrades, dependency changes, database migrations, and infrastructure migrations.
Improve storefront performance, uptime, and scalability during high traffic and sales events.
3. CI/CD and Release Automation
Build and maintain CI/CD pipelines using Jenkins, GitLab CI/CD, or GitHub Actions.
Automate build, testing, deployment, and rollback procedures.
Implement secure credential management and environment-specific configurations.
Introduce deployment approvals, health checks, smoke tests, and post-deployment validation.
Minimize downtime and deployment risks through controlled release strategies.
4. Site Reliability Engineering (SRE)
Monitor application availability, latency, traffic, errors, and infrastructure utilization.
Define and track Service Level Indicators (SLIs), Service Level Objectives (SLOs), and error budgets.
Establish incident response, escalation, root cause analysis (RCA), and corrective action processes.
Troubleshoot production incidents, including traffic spikes, bot traffic, PHP-FPM worker exhaustion, database bottlenecks, and memory issues.
Improve reliability through automation, capacity planning, and proactive failure prevention.
Participate in on-call support and production maintenance when required.
5. Monitoring, Logging, and Alerting
Configure AWS CloudWatch dashboards, metrics, alarms, and log collection.
Implement monitoring using Grafana, Prometheus, New Relic, or equivalent tools.
Monitor Nginx, PHP-FPM, MySQL, Redis, OpenSearch, Varnish, and Magento application health.
Configure actionable alerts for downtime, latency, resource exhaustion, and application errors.
Maintain incident dashboards and operational reports.
6. Security and Cost Optimization
Implement least-privilege IAM, security groups, network controls, and secure secrets management.
Configure HTTPS/TLS, AWS WAF, Cloudflare WAF, and appropriate bot protection and rate limiting.
Apply operating system and application security patches.
Secure SSH access and audit privileged access.
Optimize AWS resource utilization and reduce unnecessary cloud costs.
7. Documentation and Collaboration
Maintain infrastructure

We are looking for an experienced Blockchain Developer to design, develop, and deploy a private/permissioned blockchain network using Hyperledger Fabric.

The ideal candidate should have strong hands-on experience with Hyperledger Fabric, Node.js, Docker, Kubernetes, and cloud infrastructure, and should be able to design a production-ready blockchain architecture.

Responsibilities

- Design and implement a private blockchain network using Hyperledger Fabric
- Configure and manage:
- Organizations (Orgs)
- Peers
- Ordering Service / Orderers
- Certificate Authorities (CA)
- Channels
- MSPs
- CouchDB
- Develop and deploy Chaincode / Smart Contracts using Node.js/TypeScript
- Develop REST/gRPC APIs to interact with the blockchain network
- Implement authentication, authorization, and organization-level access control
- Design transaction and endorsement policies
- Configure private data collections where required
- Implement blockchain event listeners and notifications
- Containerize blockchain components using Docker
- Deploy the blockchain network on Kubernetes / AWS EKS
- Configure persistent storage for blockchain ledger data
- Implement monitoring, logging, and health checks
- Optimize blockchain performance and transaction throughput
- Troubleshoot peer, orderer, CA, chaincode, and networking issues
- Implement secure TLS/mTLS communication between blockchain components
- Prepare technical documentation and deployment guides

Required Skills

- Hyperledger Fabric
- Fabric CA
- Chaincode / Smart Contracts
- Node.js / TypeScript
- Docker
- Kubernetes
- AWS / EKS
- CouchDB
- PostgreSQL or relational databases
- REST APIs
- gRPC
- TLS / mTLS
- Linux
- Git

Preferred Experience

Experience with:

- Hyperledger Fabric 2.x/3.x
- Fabric Gateway
- Fabric SDK / Gateway SDK
- Kubernetes Helm
- AWS EBS / persistent volumes
- Prometheus / Grafana
- CI/CD pipelines
- Enterprise permissioned blockchain architecture
- Multi-organization blockchain networks
- High-transaction-volume systems

Deliverables

1. Complete private Hyperledger Fabric network
2. Multiple organizations with properly configured MSPs
3. Peer, Orderer, and Fabric CA infrastructure
4. Production-ready Chaincode / Smart Contracts
5. API layer for blockchain interaction
6. Docker and Kubernetes deployment configuration
7. Helm charts where applicable
8. TLS/mTLS security configuration
9. Monitoring and logging setup
10. Complete technical and deployment documentation


Location Requirement

This opportunity is open to candidates based in Karachi, Pakistan only.

Candidates should currently be living and working in Karachi and should be available for collaboration during Pakistan Standard Time (PKT).

We're building AlphaNex, a next-gen centralized crypto exchange, evolving an existing P2P system into a full CEX (trading, matching engine, market data, wallets, APIs).
We need a DevOps engineer to build our infrastructure from scratch — CI/CD, Kubernetes, cloud, monitoring, security, reliability.

Before You Apply — Review These First
- Project & Role Overview:
https://docs.google.com/document/d/1_g3Tunivbm3h5R0NHCuUEjeWjPYLsGWbjFa0uJAmEP8/
- Existing Codebase:
https://drive.google.com/drive/folders/13EJBZF3y1sJ-5L3MXtBL5gCIenusRft9/

You must review both before submitting a proposal. We want to see that you understand the current system and can identify what needs to be improved.

- What You'll Do
• Build CI/CD pipelines for microservices
• Manage cloud infra with Terraform/Ansible
• Run Docker + Kubernetes in production
• Set up monitoring (Prometheus, Grafana, ELK)
• Ensure security, HA, and disaster recovery

- What We Need
• 3+ years DevOps/SRE experience
• AWS/GCP/Azure + Terraform + Kubernetes + Docker
• CI/CD (GitHub Actions, GitLab CI, Jenkins, ArgoCD)
• Scripting (Bash, Python, Go)
• Crypto/fintech experience is a big plus

- How to Apply
Your proposal must include ALL of the following:
1. Your hourly rate (USD) + weekly availability
2. GitHub / portfolio
3. A short review of the existing system
4. One example of a CI/CD or Kubernetes system you built

Note: Proposals that do NOT include a review of the existing system will be ignored.
Individual freelancers only. No agencies. No AI-written proposals.

We're building AlphaNex, a next-gen centralized crypto exchange, evolving an existing P2P system into a full CEX (trading, matching engine, market data, wallets, APIs).
We need a DevOps engineer to build our infrastructure from scratch — CI/CD, Kubernetes, cloud, monitoring, security, reliability.

Before You Apply — Review These First
- Project & Role Overview:
https://docs.google.com/document/d/1_g3Tunivbm3h5R0NHCuUEjeWjPYLsGWbjFa0uJAmEP8/
- Existing Codebase:
https://drive.google.com/drive/folders/13EJBZF3y1sJ-5L3MXtBL5gCIenusRft9/

You must review both before submitting a proposal. We want to see that you understand the current system and can identify what needs to be improved.

- What You'll Do
• Build CI/CD pipelines for microservices
• Manage cloud infra with Terraform/Ansible
• Run Docker + Kubernetes in production
• Set up monitoring (Prometheus, Grafana, ELK)
• Ensure security, HA, and disaster recovery

- What We Need
• 3+ years DevOps/SRE experience
• AWS/GCP/Azure + Terraform + Kubernetes + Docker
• CI/CD (GitHub Actions, GitLab CI, Jenkins, ArgoCD)
• Scripting (Bash, Python, Go)
• Crypto/fintech experience is a big plus

- How to Apply
Your proposal must include ALL of the following:
1. Your hourly rate (USD) + weekly availability
2. GitHub / portfolio
3. A short review of the existing system
4. One example of a CI/CD or Kubernetes system you built

Note: Proposals that do NOT include a review of the existing system will be ignored.
Individual freelancers only. No agencies. No AI-written proposals.

Skills: Linux, Software Architecture, Blockchain, Web Development, Kubernetes, DevOps, AWS Amplify, CI/CD, Cryptocurrency

We are looking for an experienced AWS DevOps Engineer with 3+ years of hands-on experience to manage, monitor, maintain, and optimize our existing SaaS infrastructure on AWS.

Our application is already deployed, and we need a reliable DevOps engineer for long-term collaboration to ensure infrastructure stability, security, performance, and scalability.

Existing Infrastructure:
- AWS Amplify: Frontend hosting and deployment.
- Amazon EC2: CMS hosting and server management.
- Amazon ECR & ECS: Docker images and API/backend deployments.
- Auto Scaling & Load Balancing: Application scalability and availability.
- Amazon RDS (PostgreSQL): Database management.
- Redis: Caching and performance optimization.
- Amazon CloudWatch: Monitoring, logging, and alerts.

Responsibilities
- Monitor infrastructure health, application availability, logs, and performance.
- Manage ECS services, ECR images, EC2 instances, RDS, and Redis.
- Troubleshoot production issues and deployment failures.
- Maintain security, backups, and disaster recovery procedures.
- Optimize AWS costs, performance, and resource utilization.
- Support ongoing deployments, maintenance, and infrastructure improvements.

Required Experience
- Minimum 3+ years of hands-on AWS DevOps experience.
- Strong knowledge of EC2, ECS, ECR, Auto Scaling, and RDS PostgreSQL.
- Experience with Docker, Linux, CI/CD pipelines, and CloudWatch.
- Understanding of AWS networking, IAM, security, and monitoring.
- Experience managing production or SaaS infrastructure.


Application Questions
1. How many years of AWS DevOps experience do you have, and have you managed production infrastructure using ECS, ECR, EC2, RDS PostgreSQL, and Redis?
2. How would you monitor this infrastructure and troubleshoot production issues or ECS service failures?
3. What is your hourly rate, and how many hours per week can you commit to this long-term project?

Important: Please apply only if you have 3+ years of relevant, hands-on AWS DevOps experience and are interested in a long-term engagement.